我试图将合并表数据框的City.x列中的值替换为City.y列中的值,只要City.y列中没有NA。
换句话说,我想替换City.x列中除NA之外的所有值。
这是我到目前为止的代码:
library(tidyverse)
library(dplyr)
# Import food data
food <-
read_csv(file = 'https://s3.amazonaws.com/notredame.analytics.data/inspections.csv',
col_names=c("ID",
"DBAName",
"AKAName",
"License",
"FacilityType",
"Risk",
"Address",
"City",
"State",
"ZIP",
"InspectionDate",
"InspectionType",
"Results",
"Violations",
"Latitude",
"Longitude",
"Location"),
col_types = "icccffcfffcffcddc",
skip = 1)
# Change InspectionDate from character type to datetime type
food$InspectionDate <- strptime(food$InspectionDate, "%m/%d/%Y")
#Import zipcode data
zipcode <-
read_csv('https://s3.amazonaws.com/notredame.analytics.data/zipcode.csv',
col_names = c("ZIP",
"City",
"State",
"Latitude",
"Longitude"),
skip = 1)
# Convert ZIP, City, and State from character type to factor type
zipcode$ZIP <- as.factor(zipcode$ZIP)
zipcode$City <- as.factor(zipcode$City)
zipcode$State <- as.factor(zipcode$State)
#Correct zip codes (told these were incorrect)
food <- food %>%
mutate(food$ZIP = ifelse("60627", "60827", ZIP))
#Create merged table from food and zipcode tables
mergedtable <- merge(x=food,y=zipcode,by="ZIP",all.x=TRUE)
#new_DF <- mergedtable[is.na(mergedtable$ZIP),]
mergedtable <- mergedtable %>%
mutate(mergedtable$City.x = ifelse(!is.na(mergedtable$City.y), mergedtable$City.y, mergedtable$City.x))
mergedtable$City.x <- ifelse(!is.na(mergedtable$City.y), mergedtable$City.y, mergedtable$City.x)
最后两行代码都没有执行我想要的操作。第一个返回错误:
Error: unexpected '=' in:
"mergedtable <- mergedtable %>%
mutate(mergedtable$City.x ="
最后一行将mergedtable $ City.x中的值转换为数字,但我不确定数字来自何处。
这样会更容易 coalesce
library(dplyr)
mergedtable2 <- mergedtable %>%
mutate(ZIP = coalesce(City.y, City.x))
在OP的代码中,我们只需要用无引号('ZIP')来创建新列
mergedtable %>%
mutate(ZIP = ifelse(!is.na(City.y), City.y, City.x))
^^^
相似地
food <- food %>%
mutate(ZIP = ifelse("60627", "60827", ZIP))
^^^
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我来说两句